This application is a competitive revision to the currently funded add-on study of dementia and mild cognitive impairment, ?Harmonized Diagnostic Assessment of Dementia (DAD) for the Longitudinal Aging Study in India (LASI).? LASI-DAD administers in-depth cognitive tests and informant interviews, following the Health and Retirement Study's Harmonized Cognitive Aging Project (HCAP) protocol, to a sub-sample of LASI, a nationally representative survey of the health, economic, and social wellbeing of the Indian population aged 45 and older. The specific aims for this application are to: (1) Obtain expert clinical judgement-based diagnosis of dementia and mild cognitive impairment (MCI). Under the current HCAP protocol, trained interviewers administer in-depth cognitive tests and interview informants, and the diagnosis of dementia and MCI does not involve clinicians' judgment. Further investigation of risk factors of dementia and MCI depend on correct diagnostic classification. Acknowledging the importance of clinical judgment in the diagnosis of dementia and MCI, we propose a web-based approach to obtain expert clinical judgment in a cost-effective way. In this application, we propose to conduct a validation study for this web-based approach comparing it to the clinical gold standard of in-person clinical consensus diagnosis for a sub-sample and to obtain online clinical consensus diagnosis for the entire LASI-DAD sample. (2) Predict dementia and MCI risk for the LASI main sample. Although more limited compared with the LASI-DAD, the main LASI study administers a set of cognitive tests that the LASI-DAD also administers, such as orientation questions, word recall, and animal naming, and collects other relevant information, such as functional difficulties, and health history. We will develop an algorithmic model for dementia and MCI risk for the LASI main sample by calibrating the online clinical diagnosis with these information. We will then predict dementia and MCI risk at the individual level and estimate dementia and MCI prevalence at the population level. (3) Disseminate the resulting data. We will make the resulting data, including the online clinical consensus diagnosis for the LASI-DAD sample and the predicted dementia and MCI risk for the entire LASI sample, available to the larger research community.